Abstract

Object recognition and tracking is one of the most important task in the field of computer vision and surveillance system. Among many proposed, object tracking using a feature matching method is popular and accurate, however, it has a room to improve on high computational complexity and weak robustness in various environments. This paper proposes a robust object recognition and tracking method, which uses an advanced feature matching for the use of real time environment. The proposed method enables to recognize an object using invariant features, with reducing the dimension of feature descriptor, compared to the existing algorithm. The experimental results show that the proposed recognition and tracking method outperforms the conventional tracking approaches in terms of tracking accuracy and computing time.